Agentic AI Bootcamp Build Real-World RAG Apps with ChatGPT

Name: Agentic AI Bootcamp | Build RAG Apps with ChatGPT
Brand: TeacherDadaPlus

Master RAG, LangChain, FAISS & Local LLMs to Build Real-World AI Assistants (No API)

Sekhar Metla

(MSc CA) Master of Science in Computer Application

Here’s what you will learn?

Beginners who want to start learning Generative AI and Agentic AI from scratch
Students looking to build real-world AI projects and improve their portfolio
Python learners who want to apply their skills in AI development
Developers interested in RAG, LLMs, and AI automation systems
Professionals who want to upgrade their skills in AI and emerging technologies
Anyone curious about how to build ChatGPT-like AI assistants locally

This Course Includes

Recorded Lessons: 85
Recorded Hours: 7hr 32min

Certificate of completion
Access on Mobile

Course Content

85 Lessons | 7hr 32min

About the instructor

Sekhar Metla

(MSc CA) Master of Science in Computer Application

Sekhar Metla is a software engineer with 15 years of experience and a Microsoft Certified Professional. He has authored best-selling TeacherDadaPlus courses, teaching 26,000+ students across 192 countries. Holding a Master’s in Computer Applications (Software Engineering), he is known for his passionate, engaging, and motivational teaching style.

Frequently Asked Questions

This bootcamp is ideal for beginners, developers, and professionals who want to learn how to build real-world AI applications using ChatGPT and RAG systems. No advanced AI experience is required.

You will learn how to build practical AI applications using Retrieval-Augmented Generation (RAG), integrate ChatGPT, and create intelligent systems that can solve real-world problems.

Basic coding knowledge is helpful but not mandatory. The course is designed in a step-by-step manner so that even beginners can follow along and build projects.

Yes, the bootcamp focuses on hands-on learning. You will build real-world RAG-based applications using ChatGPT, which can be used in practical scenarios or added to your portfolio.

Agentic AI Bootcamp Build Real-World RAG Apps with ChatGPT

(4.9)

7hr 32min

₹479 ₹1919

Add To Cart

Subscribe to AI & Office Tools Pack

Get this course along with 17+ courses.

Agentic AI Bootcamp Build Real-World RAG Apps with ChatGPT

Sekhar Metla

Here’s what you will learn?

This Course Includes

Course Description

Course Content

Getting Started

Introduction 04m

Getting Started on Windows, MacOS, and Linux 01m

How to ask great questions 01m

FAQ’s 01m

Introduction to Agentic AI Fundamentals

Agentic AI – Introduction 05m

Difference: AI Models vs AI Agents 04m

Real-world examples of AI Agents (ChatGPT, AutoGPT, Copilots) 09m

Agentic AI is Transforming Industries Real-World Use Cases 05m

Course Roadmap and Projects Overview 08m

Generative AI Basic concepts for Everyone

Generative AI - Introduction 09m

Artificial Intelligence (AI) 06m

Machine Learning (ML) 05m

Deep Learning (DL) 06m

Setting up and Exploring the Power of ChatGPT

Generative AI (Gen AI) for Professionals 06m

Set up an account with ChatGPT 02m

How to use ChatGPT Open AI as Gen AI 08m

Environment Setup for Local Development (Hands-on)

Get and Installing Python Software 07m

Installing PyCharm – the python IDE 12m

Getting Start PyCharm IDE and futures 08m

First Python Hello World Program 05m

Getting and Installing Ollama (Local LLM) 15m

Integrating the LLaMA Model into Your Project 06m

Python Basics for AI (Quick Start)

Python Essentials for AI Projects (quick refresher) 15m

Installing libraries (OpenAI, LangChain, etc.) 11m

Installing Libraries Numpy Pandas Matplotlib 11m

Creating API keys (OpenAI / alternatives) 02m

Generative AI for Prompt Engineering – Automation

Lesson Plan Writer 05m

Create a Meeting Planer 04m

Learn Language Grammar Corrections 04m

Create a healthy diet chart for weight loss 03m

Translation for Languages 04m

Create a Product Sale Plan PPT Slides 02m

Agentic AI - Understanding LLMs (Core Engine)

What are LLMs? (GPT, Claude, Gemini) 02m

Token, prompts, and completions 03m

Prompt Engineering Basics 03m

Zero-shot vs Few-shot prompting 02m

Limitations of LLMs 03m

Fundamentals of AI Agents

What makes an AI Agent “agentic”? 03m

Components: Memory, Tools, Planning 02m

Types of Agents (Relative, Autonomous, Multi-agent) 02m

Agent Lifecycle 02m

AI Agents - Use case Design Thinking 02m

Understanding RAG - Retrieval Augmented Generation (Architecture)

What is RAG? How RAG Works 03m

Vector Databases (FAISS) 03m

Chunking & Text Splitting 07m

Retriever + Generator Pipelines 04m

Embeddings Explained 02m

LangChain for Agent Development (Framework)

Introduction to LangChain 02m

Chain vs Agents 02m

Prompt Templates 02m

Basic First RAG AI Assistant (Local, No API) (PROJECT 1 – Part 1)

Create a New Project (Python) 05m

Create new venv and activate 05m

Run to pull llama3 (Local LLM) 08m

Creating Project Structure 05m

Loading Custom Data (TXT Data) 02m

Configuring Models and DB_PATH 04m

Install langchain, faiss and other libraries 16m

Adding Ingestion code with import libs 13m

Writing loader and splitter functionality 06m

Creating Embeddings (HuggingFace) 01m

Adding FAISS Vector Database method 03m

Building RAG Pipeline (PROJECT 1 – Part 2)